India and the Global Demand for Commodities: Is there an Elephant in the Room?
Bibliographic record
Abstract
After 10 years of impressive growth, India is now the fourth largest economy in the world. Yet, to date, India's impact on global commodity markets has been muted. The authors examine how India's domestic and trade policies have distorted and constrained its demand for commodities. They find that India's industrial policies have altered the expansion path of its economy, putting the service sector to the forefront and likely reducing India's demand for metals. Sector-specific policies, such as those promoting self-sufficiency in agriculture, have altered India's demand for food commodities and its supplies of those commodities to international markets. Recent policy reforms in manufacturing have boosted output, which coincides well with an increase in India's demand for metals over the past 4–5 years. Continued policy reforms are likely to diminish the distorting influence of India's domestic and trade policies. India's demand for energy and metals should rise as some rebalancing occurs in its economic structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".